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==Abstract==
 
==Abstract==
  
We derive an algorithm for computing the wave-kernel functions cosh<math>\surd A</math>
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We derive an algorithm for computing the wave-kernel functions<math>\cos h \surd A</math> and <math>\sin h \surd A</math> for an arbitrary square matrix <math>A</math>, where <math>\sin h c z = \sin h\frac{(z)z</math>. The algorithm is based on Padé approximation and the use of double angle formulas. We show that the backward error of any approximation to $\cosh\sqrt{A}$ can be explicitly expressed in terms of a hypergeometric function. To bound the backward error we derive and exploit a new bound for $\|A^k\|^{1/k}$ that is sharper than one previously obtained by Al-Mohy and Higham [SIAM J. Matrix Anal. Appl., 31 (2009), pp. 970--989]. The amount of scaling and the degree of the Padé approximant are chosen to minimize the computational cost subject to achieving backward stability for $\cosh\sqrt{A}$ in exact arithmetic. Numerical experiments show that the algorithm behaves in a forward stable manner in floating-point arithmetic and is superior in this respect to the general purpose Schur--Parlett algorithm applied to these functions.
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==Full Document==
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<pdf>Media:Draft_Samper_112556199_4125_18m1170352.pdf</pdf>
  
 
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Revision as of 15:25, 5 May 2020

Abstract

We derive an algorithm for computing the wave-kernel functions and for an arbitrary square matrix , where Failed to parse (syntax error): \sin h c z = \sin h\frac{(z)z . The algorithm is based on Padé approximation and the use of double angle formulas. We show that the backward error of any approximation to $\cosh\sqrt{A}$ can be explicitly expressed in terms of a hypergeometric function. To bound the backward error we derive and exploit a new bound for $\|A^k\|^{1/k}$ that is sharper than one previously obtained by Al-Mohy and Higham [SIAM J. Matrix Anal. Appl., 31 (2009), pp. 970--989]. The amount of scaling and the degree of the Padé approximant are chosen to minimize the computational cost subject to achieving backward stability for $\cosh\sqrt{A}$ in exact arithmetic. Numerical experiments show that the algorithm behaves in a forward stable manner in floating-point arithmetic and is superior in this respect to the general purpose Schur--Parlett algorithm applied to these functions.

Full Document

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2 The main text

3 Bibliography

4 Acknowledgments

5 References

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Document information

Published on 01/01/2018

DOI: 10.1137/18M1170352
Licence: CC BY-NC-SA license

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